The goal is to provide integrated resources for enrolling eligible subjects, collecting clinical data and biological samples, and providing design and data analytic services to support all PPG investigators. Moreover, we will provide comprehensive data management services. We will provide a broad range of collaborations by assisting with study design, biostatistical analyses, interpretation iof results, and manuscript preparation. In particular, co-investigators will provide specialized expertise in functional genomics, analytic methods for characterizing the relationships among high-dimensional molecular level data and clinical outcomes, analytic methods for gene expression data arising from microarray technologies, and innovative methods for analysis of the proteomics data. The Specific Aims are: 1. Clinical: (a) Continue the previous NHLBI SCOR in Acute Lung Injury (ALl SCOR) prospective cohort of major trauma patients ("Trauma Cohort") who are at high risk for developing ALl within 5 days of trauma;(b) utilize the Trauma Cohort to provide eligible subjects and biological samples;(c) continue the previous ALl SCOR's system to collect clinical data and biological samples from patients enrolled in Trauma Cohort. 2. Biostatistical: (a) Advise investigators on study design issues, including sample size and power considerations;(b) conduct statistical analyses of data from laboratory projects and risk factor model development for clinical investigations to address specific research hypotheses defined in the project-specific proposals;(c) assist with preparation for and writing of interim and final reports, presentations, abstracts, and manuscripts;(d) conduct exploratory analyses that may lead to generation of new hypotheses. 3. Data Management: (a) Modify and implement the Data Management System (DMS) for the Trauma Cohort;(b) provide training and assistance for research staff;(c) conduct all phases of quality assurance, validation, query resolution and reporting for clinical studies;(d) create valid datasets of high scientific quality, combining data from multiple sources for biostatistical analyses.